Wastewater treatment plants with enhanced biological phosphorus removal represent a state-of-the-art technology. Nevertheless, the process of phosphate removal is prone to occasional failure. One ...reason is the lack of knowledge about the structure and function of the bacterial communities involved. Most of the bacteria are still not cultivable, and their functions during the wastewater treatment process are therefore unknown or subject of speculation. Here, flow cytometry was used to identify bacteria capable of polyphosphate accumulation within highly diverse communities. A novel fluorescent staining technique for the quantitative detection of polyphosphate granules on the cellular level was developed. It uses the bright green fluorescence of the antibiotic tetracycline when it complexes the divalent cations acting as a countercharge in polyphosphate granules. The dynamics of cellular DNA contents and cell sizes as growth indicators were determined in parallel to detect the most active polyphosphate-accumulating individuals/subcommunities and to determine their phylogenetic affiliation upon cell sorting. Phylotypes known as polyphosphate-accumulating organisms, such as a "Candidatus Accumulibacter"-like phylotype, were found, as well as members of the genera Pseudomonas and TETRASPHAERA: The new method allows fast and convenient monitoring of the growth and polyphosphate accumulation dynamics of not-yet-cultivated bacteria in wastewater bacterial communities.
The advent of high-throughput genotyping technologies coupled to genomic prediction methods established a new paradigm to integrate genomics and breeding. We carried out whole-genome prediction and ...contrasted it to a genome-wide association study (GWAS) for growth traits in breeding populations of Eucalyptus benthamii (n =505) and Eucalyptus pellita (n =732). Both species are of increasing commercial interest for the development of germplasm adapted to environmental stresses.
Predictive ability reached 0.16 in E. benthamii and 0.44 in E. pellita for diameter growth. Predictive abilities using either Genomic BLUP or different Bayesian methods were similar, suggesting that growth adequately fits the infinitesimal model. Genomic prediction models using ~5000-10,000 SNPs provided predictive abilities equivalent to using all 13,787 and 19,506 SNPs genotyped in the E. benthamii and E. pellita populations, respectively. No difference was detected in predictive ability when different sets of SNPs were utilized, based on position (equidistantly genome-wide, inside genes, linkage disequilibrium pruned or on single chromosomes), as long as the total number of SNPs used was above ~5000. Predictive abilities obtained by removing relatedness between training and validation sets fell near zero for E. benthamii and were halved for E. pellita. These results corroborate the current view that relatedness is the main driver of genomic prediction, although some short-range historical linkage disequilibrium (LD) was likely captured for E. pellita. A GWAS identified only one significant association for volume growth in E. pellita, illustrating the fact that while genome-wide regression is able to account for large proportions of the heritability, very little or none of it is captured into significant associations using GWAS in breeding populations of the size evaluated in this study.
This study provides further experimental data supporting positive prospects of using genome-wide data to capture large proportions of trait heritability and predict growth traits in trees with accuracies equal or better than those attainable by phenotypic selection. Additionally, our results document the superiority of the whole-genome regression approach in accounting for large proportions of the heritability of complex traits such as growth in contrast to the limited value of the local GWAS approach toward breeding applications in forest trees.
Large areas of tropical forests have been lost through deforestation, resulting in fragmented forest landscapes. However, the dynamics of forest fragmentation are still unknown, especially the ...critical forest edge areas, which are sources of carbon emissions due to increased tree mortality. We analyzed the changes in forest fragmentation for the entire tropics using high-resolution forest cover maps. We found that forest edge area increased from 27 to 31% of the total forest area in just 10 years, with the largest increase in Africa. The number of forest fragments increased by 20 million with consequences for connectivity of tropical landscapes. Simulations suggest that ongoing deforestation will further accelerate forest fragmentation. By 2100, 50% of tropical forest area will be at the forest edge, causing additional carbon emissions of up to 500 million MT carbon per year. Thus, efforts to limit fragmentation in the world’s tropical forests are important for climate change mitigation.
Polyadenylation at the 3'-end is a major regulator of messenger RNA and its length is known to affect nuclear export, stability, and translation, among others. Only recently have strategies emerged ...that allow for genome-wide poly(A) length assessment. These methods identify genes connected to poly(A) tail measurements indirectly by short-read alignment to genetic 3'-ends. Concurrently, Oxford Nanopore Technologies (ONT) established full-length isoform-specific RNA sequencing containing the entire poly(A) tail. However, assessing poly(A) length through base-calling has so far not been possible due to the inability to resolve long homopolymeric stretches in ONT sequencing. Here we present
, an R package to estimate poly(A) tail length on ONT long-read sequencing data.
operates on unaligned, base-called data. It measures poly(A) tail length from both native RNA and DNA sequencing, which makes poly(A) tail studies by full-length cDNA approaches possible for the first time. We assess
's performance across different poly(A) lengths, demonstrating that
is a versatile tool providing poly(A) tail estimates across a wide range of sequencing conditions.
Constantly decreasing costs of high-throughput profiling on many molecular levels generate vast amounts of multi-omics data. Studying one biomedical question on two or more omic levels provides ...deeper insights into underlying molecular processes or disease pathophysiology. For the majority of multi-omics data projects, the data analysis is performed level-wise, followed by a combined interpretation of results. Hence the full potential of integrated data analysis is not leveraged yet, presumably due to the complexity of the data and the lacking toolsets. We propose a versatile approach, to perform a multi-level fully integrated analysis: The Knowledge guIded Multi-Omics Network inference approach, KiMONo ( https://github.com/cellmapslab/kimono ). KiMONo performs network inference by using statistical models for combining omics measurements coupled to a powerful knowledge-guided strategy exploiting prior information from existing biological sources. Within the resulting multimodal network, nodes represent features of all input types e.g. variants and genes while edges refer to knowledge-supported and statistically derived associations. In a comprehensive evaluation, we show that our method is robust to noise and exemplify the general applicability to the full spectrum of multi-omics data, demonstrating that KiMONo is a powerful approach towards leveraging the full potential of data sets for detecting biomarker candidates.
Abstract
The Cpx-envelope stress system coordinates the expression and assembly of surface structures important for the virulence of Gram-negative pathogenic bacteria. It is comprised of the ...membrane-anchored sensor kinase CpxA, the cytosolic response regulator CpxR and the accessory protein CpxP. Characteristic of the group of two-component systems, the Cpx system responds to a broad range of stimuli including pH, salt, metals, lipids and misfolded proteins that cause perturbation in the envelope. Moreover, the Cpx system has been linked to inter-kingdom signalling and bacterial cell death. However, although signal specificity has been assumed, for most signals the mechanism of signal integration is not understood. Recent structural and functional studies provide the first insights into how CpxP inhibits CpxA and serves as sensor for misfolded pilus subunits, pH and salt. Here, we summarize and reflect on the current knowledge on signal integration by the Cpx-envelope stress system.
In this article, the authors define a methodological framework for analyzing the relationship between state sequences and covariates. Inspired by the principles of analysis of variance, this approach ...looks at how the covariates explain the discrepancy of the sequences. The authors use the pairwise dissimilarities between sequences to determine the discrepancy, which makes it possible to develop a series of statistical significance–based analysis tools. They introduce generalized simple and multifactor discrepancy-based methods to test for differences between groups, a pseudo-R
2 for measuring the strength of sequence-covariate associations, a generalized Levene statistic for testing differences in the within-group discrepancies, as well as tools and plots for studying the evolution of the differences along the time frame and a regression tree method for discovering the most significant discriminant covariates and their interactions. In addition, the authors extend all methods to account for case weights. The scope of the proposed methodological framework is illustrated using a real-world sequence data set.
Nature‐based solutions to flood risk management, such as engineered logjams (ELJs), contribute to the reintroduction of wood in rivers. As part of stream restoration, and utilized in tributaries, ...ELJs increase upstream water levels, causing the flow to spill onto surrounding floodplains, resulting in the desynchronization of peak flows in a river network. To understand the effect of ELJs on local river hydrodynamics, we experimentally investigate the flow field upstream and downstream of six ELJs, using acoustic Doppler velocimetry and flow visualization. We consider channel‐spanning structures designed with a gap (b0) underneath, allowing unhindered baseflow. Our results revealed that upstream of the logjams, flow diverted toward the lower gap, creating a primary jet exiting underneath the structures, whose strength depends on the physical logjam design. Maximum jet velocities remained constant until a downstream distance of 4b0 for all logjams. The upper wake was structure‐dependent, with logjam structures allowing distinct internal flow paths generating secondary jets, which influenced near wake decay (x < 4b0) and turbulent mixing. The highest turbulence in the near wake was found for the non‐porous and short, porous logjam designs, while the upper wake of all long, porous logjams was characterized by low turbulent kinetic energy levels. Far wake decay (x > 4b0) was self‐similar for all logjams and resulted in near flow recovery at downstream streamwise distances greater than 35b0. ELJs are likely to enhance bed shear stress, increasing the risk of local scour and sediment mobilization. Our study expands the current knowledge of ELJ hydrodynamics and highlights potential implications for the riverine ecosystem.
Plain Language Summary
Engineered logjams (ELJs) with a lower gap are a nature‐based solution for flood risk management and river restoration. Channel‐spanning wooden logjams increase upstream water levels, causing the flow to spill onto surrounding floodplains, slowing down surface and ground water through the catchment. Using experimental flow velocity measurements in a laboratory open channel flume, we investigated the local flow field upstream and downstream of six ELJs. We demonstrate that the flow blockage caused by ELJs resulted in an increase in upstream flow depth, with a lower velocity at logjam height, and higher velocity at gap height which extended into the downstream region. While this high‐velocity stream was present for all logjams with a lower gap, the downstream flow field at logjam height was dependent on logjam design. Porous ELJs allowing flow through the structure, for instance, generated smaller, weaker streams which influenced the flow field. Independent of the logjam design, the flow field recovered to its original, undisturbed flow field at nearly the same downstream distance. Our study highlights the flow alterations associated with different physical logjam designs and raises potential secondary impacts on the riverine ecosystem such as local scouring, sediment mobilization, and trapping as well as the enhancement in habitat complexity.
Key Points
We experimentally investigated the impact of six non‐porous and porous engineered logjams on upstream and downstream channel hydrodynamics
Main gap below logjams produced a wall jet, with maximum jet velocity dependent on channel blockage
Highly turbulent near wake observed for non‐porous and short logjams, with long porous jams characterized by lower turbulent kinetic energy
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